Despite increases in autoimmune disease within our aging population, the mechanisms by which autoimmune cells are generated, programmed, and maintained are not well understood. It is clear that epigenetic processes participate in many autoimmune diseases, including systemic lupus erythematosus (SLE), but the precise mechanism and overall processes that they regulate are incompletely defined. Epigenetic traits act in concert on chromatin structure, modulating the accessibility of DNA to transcription factors that activate or repress transcriptional programs, and in effect control the molecular and phenotypic potential of cells. A complete understanding of the epigenetic mechanisms of autoimmunity is therefore crucial to our understanding of autoimmune disease and the development of better and more effective therapeutics and diagnostics. To this end, we have developed a robust experimental and informatic pipeline for determining the epigenetic landscapes and transcriptomes from small numbers of cells. Here, we propose to bring this technology to study SLE with the Emory ACE investigators, and develop both basic science and mechanistic projects within the ACE network. Through our Collaborative Project with Dr. Sanz, we have examined the transcriptomes and epigenomes of five B subsets of SLE, representing naive, activated, and memory states. We found: a) that the DN2 B cell subset, which is greatly expanded during SLE flares, has a close epigenetic and transcriptional relationship to plasmablasts and may arise through an extrafollicular mechanism that includes TLR signaling; b) that resting naive B cells in SLE patients already possess a disease signature; and c) that the SLE epigenome/transcriptome is driven in part by the transcription factors ATF3 and EGR4. Despite these advances, significant gaps remain. For example, we do not know whether the SLE epigenetic/transcription signature is: i) imprinted in immature or progenitor B cell populations; ii) stable; or iii) common to other autoimmune diseases. We also do not know if iv) healthy cells exist within an SLE patient's B cell subsets and v) how much variability exists between cells within a subset. To address these gaps, in Aim 1, we will use bulk and single cell RNA-seq technologies to identify the unique and variable features of: autoimmune cells from immature and mature B cell populations of SLE and other diseases; and from reemerging B cell populations following B cell depletion therapies. Aim 2, will address the same gaps in knowledge as Aim 1 but complement those data through examination of the epigenetic pathways that program the autoimmune cells. This will be accomplished by assessing the DNA methylation, histone code of enhancers and promoters, and the chromatin accessible landscape of autoimmune and healthy control cells. We will also test the stability of the SLE epigenetic signature using an ex vivo differentiation assay. We will integrate these datasets to identify genes, pathways, and transcription factor networks that define the unique features of autoimmune cells and generate a molecular model of autoimmunity. The results will also identify numerous potential novel biomarkers that can aid in diagnostics and prognoses.